Image quality assessment plays an important role in the development and validation of various image and video applications, such as compression and enhancement. Objective quality models are usually classified based on the availability of reference images. If an undistorted reference image is available, the quality metric is considered as a full reference (FR) assessment method. Several image and video applications require that the quality be assessed in real-time. Consequently, the computational complexity associated with a quality assessment method becomes an important issue to address. Another important factor to consider is the accuracy of the quality assessment method, which indicates how well computed quality scores correspond with the opinions of human beings.
Accordingly, a method and system to improve the accuracy of a quality assessment method of low complexity is required.